Development of a national pain management competency profile to guide entry-level physiotherapy education in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: National strategies from North America call for substantive improvements in entry-level pain management education to help reduce the burden of chronic pain. Past work has generated a valuable set of interprofessional pain management competencies to guide the education of future health professionals. However, there has been very limited work that has explored the development of such competencies for individual professions in different regions. Developing profession-specific competencies tailored to the local context is a necessary first step to integrate them within local regulatory systems. Our group is working toward this goal within the context of entry-level physiotherapy (PT) programs across Canada. AIMS: This study aimed to create a consensus-based competency profile for pain management, specific to the Canadian PT context. METHODS: A modified Delphi design was used to achieve consensus across Canadian university-based and clinical pain educators. RESULTS: Representatives from 14 entry-level PT programs (93% of Canadian programs) and six clinical educators were recruited. After two rounds, a total of 15 competencies reached the predetermined endorsement threshold (75%). Most participants (85%) reported being "very satisfied" with the process. CONCLUSIONS: This process achieved consensus on a novel pain management competency profile specific to the Canadian PT context. The resulting profile delineates the necessary abilities required by physiotherapists to manage pain upon entry to practice. Participants were very satisfied with the process. This study also contributes to the emerging literature on integrated research in pain management by profiling research methodology that can be used to inform related work in other health professions and regions.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it